We consider the empirical likelihood method for estimation of distribution and quantile functions where side information is incorporated through moment conditions. We systematically study the asymptotic properties of the estimators, such as the uniform strong laws of large numbers and weak...

type="main" xml:id="sjos12060-abs-0001" <title type="main">ABSTRACT</title>Although efficiency robust tests are preferred for genetic association studies when the genetic model is unknown, their statistical properties have been studied for different study designs separately under special situations. We study some...

It is known that in many missing data models, for example, survival data models, some parameters are root-n estimable while the others are not. When they are, their limiting distributions are often Gaussian and easy to use. When they are not, their limiting distributions, if exists, are often...

We study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL...

In classical Bayesian inference the prior is treated as fixed, it is asymptotically negligible, thus any information contained in the prior is ignored from the asymptotic first order result. However, in practice often an informative prior is summarized from previous similar or the same kind of...